Diet, Dollars, & Destiny- rethinking links in the food chain-

David L. Katz, MD, MPH, FACPM, FACPAssociate Professor, adjunct, Public Health Practice

Director, Prevention Research Center

Yale University School of MedicineYale University School of Medicine

President, Turn the Tide Foundation, Inc.

www.davidkatzmd.com

CAPILeaders Summit

on Food

Montreal, Québec

2-17-10

A look before the leap-

Of diet & destiny What food could do Not just lives, but also dollars Reciprocal back scratching Nu tool for a Nu age problem: NuVal The Nu value proposition Money where mouths are? It’s a SNAP Sustainability, Viability, Vitality; Citius,

Altius, Fortius and our Olympic moment Rings, links, chains and circles

Of diet & destiny…

There is Lifestyle… and everything else

McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA. 1993;270:2207-12

Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA. 2004;291:1238-45

Strong K, Mathers C, Leeder S, Beaglehole R. Preventing chronic diseases: how many lives can we save? Lancet. 2005 Oct 29-Nov 4;366(9496):1578-82

Epping-Jordan JE, Galea G, Tukuitonga C, Beaglehole R. Preventing chronic diseases: taking stepwise action. Lancet. 2005 Nov 5;366(9497):1667-71

The Master Levers of Destiny- Feet Forks

Fingers

Nurturing Nature: the leverage of living well-

Ornish D et al. Intensive lifestyle changes for reversal of coronary heart disease. JAMA. 1998;280:2001-7

Ornish D et al. Changes in prostate gene expression in men undergoing an intensive nutrition and lifestyle intervention. Proc Natl Acad Sci U S A. 2008 ;105:8369-74

The People in Pottsdam-

Ford ES, Bergmann MM, Kröger J, Schienkiewitz A, Weikert C, Boeing H. Healthy living is the best revenge: findings from the European Prospective Investigation Into Cancer and Nutrition-Potsdam study. Arch Intern Med. 2009 Aug 10;169(15):1355-62

But…

Knowledge, alas, isn’t power…

Katz DL. Life and death, knowledge and power: why knowing what matters isn’t what's the matter. Arch Intern Med. 2009 Aug 10;169(15):1362-3

What food could do-

80% reduction in heart disease

90% reduction in diabetes

60% reduction in cancer

and so on…

Not JUST lives, but also dollars…

by 2018 over 100 million Americans will be obese

we will be spending roughly $340 billion annually on obesity, a tripling of current levels

per capita spending will rise from $361 to over $1400 a year

http://www.fightchronicdisease.org/pdfs/CostofObesityReport-FINAL.pdf November, 2009

Reciprocal back scratching-

Agriculture & Health: anybody itchy? Health sector needs help addressing the

enormous impact of food on health Agriculture sector needs help addressing the

needs of eaters in tandem with the needs of feeders

So: each scratches the other’s back… Health sector helps subsidize agricultural innovations

that promote health Health sector saves more money than it spends by

reducing chronic disease burden* Ag sector has infusion of support from a whole new

area, and maintains or enhances current profits, while contributing to the public good

Everybody wins… and winds up less itchy*e.g., Diabetes Prevention

Program

To encourage the consumption of ‘good’ food…

we have to help people find it.

Good advice…

“Eat food, not too much, mostly plants.” Michael Pollan

…can be hard to follow!-

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People need to know things-they never knew they never knew!…

Sodium content per 100 calories?

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Sodium 233 mg

Sodium 131 mg

Sodium 73 mg

Sodium 100 mg

18

Added sugar per 100kcal?

19

Sugar 12 G

Sugar 11 G

Which one of these products is the more nutritious choice?

Nutrition Quiz – Peanut Butter

Nutrition Quiz – Peanut Butter

Answer: Regular Peanut Butter

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A little nutty…

NutrientPeanut Butter Reduced Fat

Peanut ButterSodium 150mg 250mg

Total Carbohydrate/sugar 7g 15g

Added Sugar* 3g 4g

Saturated Fat/Trans Fat 3g/0g 2.5g/0g

Fiber 2g 1g

Calories 190/32g 190/36g

NuVal SCORE 23 17

Nu tool for a Nu age problem: NuVal

What FDA or IOM should have done:

July, 2003 Katz DL. A food supply for dummies. Op-Ed: Hartford

Courant; NY Newsday; etc. 10/03

Feb, 2006: If you want something done… and the rest is history…

ONQI Scientific Expert/Development Panel Chair: Dr. David Katz, Yale University School of Medicine

Dr Keith Ayoob, Albert Einstein College of Medicine Dr Leonard Epstein, University of Buffalo; inventor, Traffic Light Diet Dr David Jenkins, University of Toronto; inventor, Glycemic Index Dr Francine Kaufman, USC; Past President, American Diabetes Association Dr Robert Kushner, Northwestern University Dr Ronald Prior, Arkansas Children’s Nutrition Center, USDA HNRC Dr Rebecca Reeves, Past President, American Dietetic Association Dr Barbara Rolls, Pennsylvania State University Dr Sachiko St. Jeor, University of Nevada Dr John Seffrin, President & CEO, American Cancer Society Dr Walter Willett, Harvard University

16 invitations extended; 14 acceptances

Project Coordinators: Debbie Kennedy, PhD; Zubaida Faridi, MD, MPH: PRC Statistician/Data Analyst: Valentine Njike, MD, MPH: PRC Dietitians: Judy Treu, MS, RD; Lauren Rhee, MS, RD: PRC

Others consulted

ONQI Scientific Advisory Board

Dr. David Katz, Ex Officio, Yale University

Dr. Keith Ayoob, Chair, Albert Einstein College of Medicine

Dr. Leonard Epstein, University of Buffalo; inventor, Traffic Light Diet

Dr. David Jenkins, University of Toronto; inventor, Glycemic Index Dr. Sonia Caprio, Yale University Dr. Rebecca Reeves, Past President, American Dietetic Association Dr. Gail Frank, California State University Dr. Eric Decker, University of Massachusetts; food science

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The ONQI Algorithm-Numerator Denominator

FiberFolateVitamin AVitamin CVitamin DVitamin EVitamin B12Vitamin B6PotassiumCalciumZincOmega-3 fatty acidsTotal bioflavanoidsTotal carotenoidsMagnesiumIron

Saturated fatTrans fatSodiumSugarCholesterol

•Macronutrient AdjustorsFat qualityProtein qualityGlycemic loadEnergy density

•Trajectory Scores•Weighting Coefficients

Categorical stipulations

• Pure foods vs. processed

• Intrinsic vs. added sugars

• Artificial sweeteners• Etc.

A trajectory score answers this question:

How does the concentration of a given nutrient in a

given food compare to the recommended

concentration of that nutrient in the diet overall?

Trajectory score generation-

Sodium C3=sodium/energy/1.2;

Calcium Da1=calcium/energy/0.5;

Weighting coefficients…because a difference, to be a difference, must make a difference

Applied to all trajectory scores

Ws = severity

Wp = prevalence

Wr = relative impact / strength of association

ONQI formulaSomething like:

(1+UA1)×(1+UA2)×(1+ WP1×WS1×WR1×(adjustedTS1)+ ------------------ +WP16× WS16× WR16×(adjustedTS16 ))

__________________________________________________________________

GL×ED×(1+WP1×WS1×WR1×(adjustedTS1)+ ---- +WP5×WS5×WR5×(adjustedTS5))

Variables in Formula TS = trajectory score Wp = weighting coefficient, prevalence Ws = weighting coefficient, severity Wr= weighting coefficient, relative impact UA1= adjuster for biological quality of fat UA2= adjustor for biological quality of protein ED= energy density adjuster GL= glycemic load adjuster Adjusted= pertinent mathematical transformations

And in all its (gore or) glory: 20 pages of mind-numbing computer programming

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WHEAT FLOURNIACINREDUCED IRONTHIAMINERIBOFLAVINFOLIC ACIDSOYBEAN OILSUGARCOTTONSEED OILSALTBAKING SODAHF CORN SYRUPSOY LECITHINNATURAL FLAVORCORNSTARCH

10 g 1 mg 2 mg 1 mg .5 mg 24 mg 1 g .75 g .5 g135 mg120 mg100 mg 70 mg 40 mg 10 mg

INGREDIENTS: ENRICHED FLOUR (WHEAT FLOUR, NIACIN, REDUCED IRON, THIAMINE MONONITRATE [VITAMIN B1], RIBOFLAVIN [VITAMIN B2], FOLIC ACID), SOYBEAN OIL, SUGAR, PARTIALLY HYDROGENATED COTTONSEED OIL, SALT, LEAVENING (BAKING SODA AND/OR CALCIUM PHOSPHATE), HIGH FRUCTOSE CORN SYRUP, SOY LECITHIN (EMULSIFIER), NATURAL FLAVOR, CORNSTARCH.

“Recipe”Development(imputation)

NutrientProfile

High-octane fuel for a high performance engine:

RECIPE

NuVal has built a database to house scores and nutrition information unlike any other in the country (world?). Key content

• Product ingredients and nutritional content.• Product images (front, back, and nutritional panel)• IRI category reference• Product scores

Key Functionality• UPC search (8, 11, 13 digit formats supported)• Brand and product name search• Ingredient exclusion (gluten, nut, etc) searches• Standardized data formats (flat file import and export)• Automated cross reference based on nutritional profiles

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Power in the Database

Vrrrooommm-

Under the Hood:

undeniable (& distinctly advantageous) complexity

At the User Interface:

turnkey simplicity

A Sampling of Scores

Beef & PoultrySeafoodTurkey Breast (skinless) 48

Chicken Breast (boneless) 39Pork Tenderloin 35Bottom Round Roast (Beef) 34Flank Steak (Beef) 34Breast 31Veal Chop 31Veal Leg Cutlet 31Beef Tenderloin 30Chicken Drumstick 30Ground Sirloin (Beef 90/10) 30Pork Chop (boneless center) 28Chicken Wings 28Ground Round (Beef 85/15) 28Lamb Chops (loin) 28Leg of Lamb 28Ham (whole) 27Ground Chuck (Beef 80/20) 26Pork Ribs, Country Style 25Beef Spareribs 24Pork Baby Back Ribs 24

Atlantic Salmon Fillet 87Atlantic Halibut Fillet 82Catfish Fillet 82Cod Fillet 82Tilapia Fillet 82Oysters 81Swordfish Steak 81Prawns 75Shrimp 75Clams 71Monkfish Fillet 64Bay Scallops 51Turbot Fillet 51Lobster 36

Birds Eye Frozen Cauliflower Floret plastic bag 100Birds Eye Frozen Chopped Spinach box 100Green Giant Frozen Broccoli Cuts steamable bag 100Green Giant Frozen Cut Green Beans steamable bag 100Birds Eye Frozen Peas polybag 96La Choy Frozen Snow Pea Pods box 96Birds Eye Steamfresh Frozen Brussels Sprouts steamable bag 94Birds Eye Frozen Cooked Winter Squash box 91Green Giant Frozen Mixed Vegetables steamable bag 87Birds Eye Frozen Asparagus Stir Fry plastic bag 82Birds Eye Frozen Green Beans & Lightly Toasted Almonds box 68Green Giant Frozen Cauliflower & 3 Cheese Sauce plastic bag 42Green Giant Frozen Creamed Spinach in Low-Fat Sauce box 34Birds Eye Steamfresh Specially Seasoned Southwestern Corn 33Green Giant Frozen Sweet Baby Peas and Low-Fat Butter Sauce 30Green Giant Frozen Honey Glazed Carrots box 26Green Giant Frozen Green Bean Casserole box 23

Apricots 100Asparagus 100Beans 100Blueberries 100Broccoli 100Cabbage 100Cauliflower 100Kiwi 100Lettuce 100Mustard Greens 100Okra 100Orange 100Spinach 100Strawberries 100Turnip 100Carrots 99Grapefruit 99Pineapple 99Plums 99Mango 93Potatoes 93Red onions 93Tangerines 93Bananas 91Corn 91Grapes 91Honeydew Melon 91Rhubarb 91Iceberg Lettuce 82Bok Choy 81Passion Fruit 78Coconut 24

Produce

Canned VegetablesCanned Vegetables

Frozen VegetablesFrozen Vegetables

Del Monte Fresh Cut French Style Green Beans No Salt 100Del Monte Fresh Cut Whole Leaf Spinach 76Del Monte Fresh Cut Sweet Corn Cream Style No Salt Added 67Del Monte Fresh Cut Whole Green Beans 59Green Giant Extra Long Tender Green Asparagus Spears 56Green Giant Cut Green Beans 52Del Monte Organic Whole Kernel Corn 50Green Giant Sweet Peas 50% Less Sodium 48Le Sueur Very Young Small Sweet Peas 43Green Giant Super Sweet Yellow & White Whole Kernel Corn 42Del Monte Organic Sweet Peas 39Veg-All Homestyle Large Cut Vegetables 35Del Monte Fresh Cut Sweet Corn Cream Style 32Green Giant Niblets Whole Sweet Corn 27Progresso Artichoke Hearts 18Aunt Nellie's Whole Ruby Red Pickled Beets 3

Hodgson Mill Unprocessed Wheat Bran 100Post Shredded Wheat Original 91Kashi 7 Whole Grain Puffs 91Kellogg's All-Bran 76Kellogg's Special K Protein Plus 60Quaker Shredded Wheat 56General Mills Fiber One 52Kashi Golean High Protein & High Fiber 47General Mills Cinnamon Toast Crunch 40Quaker Instant Oatmeal Original 39General Mills Cheerios 34Post Shredded Wheat Frosted 31Kellogg's All-Bran 31Post HealthyClassics Grape-Nuts 30Post Honey Bunches Of Oats with Almonds 29Kashi 7 Whole Grain Flakes 29General Mills Kix 29General Mills Wheaties 28General Mills Whole Grain Total Raisin Bran 27Post Healthy Classics Raisin Bran 26Kellogg's Frosted Flakes 26Kellogg's Corn Flakes 25Post Fruity Pebbles 24Kellogg's Mueslix 24General Mills Corn Chex 24Cream Of Wheat Instant Hot Cereal 24Quaker Natural Granola Oats, Honey & Raisins 23Kellogg's Rice Krispies 23General Mills Basic 4 23General Mills Lucky Charms 23Kellogg's Corn Pops 20Kellogg's Froot Loops 17Kashi Strawberry Fields 11Cap'n Crunch 10Quaker Instant Grits Butter Flavor 6

Garden of Eatin No Salt Blue Tortilla Chips 52Terra unsalted potato chips barbecue 41Garden of Eatin Blue Tortilla Chips 40Terra Gold Original Potato Chips 33Snyder's Multigrain Pretzel Sticks Lightly Salted 31Guiltless Gourmet Chili Lime Tortilla Chips 30Tostitos Light Restaurant Style 28Utz Baked Potato Crisps Original 27Good health peanut butter filled pretzels 26Doritos Baked Nacho Cheese 25Frito-Lay Sun Chips Harvest Cheddar 25Lay's Baked Potato Crisps 25Baked Ruffles Cheddar & Sour Cream 24Newman's Own Organic Pretzel Rounds Unsalted 24Ruffles Thick Cut Original 24Doritos Cool Ranch 23Lay's Potato Chips Classic 23Snyder's Pretzels Honey Wheat o 23Sunshine cheez-it party mix 20Newman's Own Organic Pretzel Rounds Salted 19Fritos Corn Chips Original 16Cheetos Puffs 14Rold Gold Petzels Rods 14Chex Mix Traditional 13Doritos Nacho Cheese 10Rold Gold Pretzel Sticks Fat Free 10Pringles Reduced Fat Original 9Ruffles Cheddar & Sour Cream 9Cheetos Crunchy 5Utz Potato Chips Barbecue 4Combos Pretzel Cheddar Cheese 3Bugles Original Corn Snack 2Glutino Pretzel Twists Gluten Free 1

CerealCereal Salty SnacksSalty Snacks

NuVal con tempo >40,000 foods scored and audited Live in 526 supermarkets in 19 states; rolling out to more this year Searchable on-line database in April, 2010

Consumer Testing, because:A difference, to be a difference…

must make a difference. Gertrude Stein

Am J Health Promot. 2009

Face Validity: Consumer Testing Qualitative: focus groups Quantitative: Affinova

Group 1: women, n = 454 Group 2: men and women, n = 350

Percent of Respondents Answering “strongly agree” or “agree” (n=454) The system would be useful in helping me make my purchasing

decision: 93% The rating system would affect the decisions I make about which foods

to purchase in the grocery store: 86% I would be more likely to purchase a product that used the system

versus one that did not: 74% I would be more likely to stop at a grocery store that used the system

versus one that did not: 66%

Am J Health Promot. 2009

Consumer Testing: ONQI vs. Alternative (best, better, good, no score)

Which store would consumers select if both systems were available nearby? (n = 350)

Definitely/Probably ONQI 75% Either Store 20% Definitely/Probably Alternative 2% Neither Store 3%

Consumer Research: Key Findings

The system is universally appealing to all sub-groups

Consumers overwhelmingly confirm the value of a nutritional scoring system

The presence of the ONQI graphic leads to higher purchase intent, versus a product that does not show the ONQI icon, even in combination with a manufacturer’s nutrition symbol

The ONQI system is preferred to systems offering less ‘granular’ information

*Consumer Testing: Knowledge, Attitudes, Behavior

Consumer In-Store InterceptsConsumer In-Store Intercepts

Consumer Panel Online SurveysConsumer Panel Online Surveys

Retailer Receipt SurveysRetailer Receipt Surveys

Tracking Sales Movement Tracking Sales Movement In and across categoriesIn and across categories Both generally and for NuVal-aware participantsBoth generally and for NuVal-aware participants Shift to higher-nutrition choicesShift to higher-nutrition choices

*conducted by NuVal independently, and in conjunction with retail partners

NuVal is going to school…

Independence School District, MO New Haven, CT ?~ Palm Beach County, FL

…But has already been tested:

validation research

Am J Health Promot. 2009;24:133-43

Construct Validity: proof in the pudding (& elsewhere…)

Food Category Rho p-value Diverse (n=21) 0.92 <0.001 Bread and Crackers (n=10) 0.66 0.04 Cereals & Granola Bars (n=10) 0.89

<0.001 Dairy Products (n=9) 0.92 <0.001 Fat/Oil (n=10) 0.71 0.02 Fruits (n=10) 0.33 0.36 Meat/Protein (n=10) 0.93 <0.001 Snack Foods (n=9) 0.93 <0.001 Spreads and Condiments (n=10) 0.95

<0.001 Vegetables (n=10) 0.70 0.02

In press: Am J Clin Nutr; 4/10

A quick DASH toward validation-

7 days of DASH study meal plan at 2300mg Na level Composite recipe scoring technique

Mean ONQI score: 46* (95% CI: 40 to 53)

NHANES 2003-2006 cohort (n = 15,900) Composite recipe scoring technique

Mean ONQI score: 26.5* (95% CI: 26.4 to 26.6) Correlation with quartiles of HEI-2005: R = 0.52; p<0.0001

*p<0.01

In press: Am J Clin Nutr; 4/10

Table 1. Descriptive statistics for Overall Nutritional Quality Index (ONQI) and HundredScale (NuVal 0-100) values, and percentage of population having diets at NuVal levels1, 2 Total Population Index of Diet Quality (n = 15,900) Overall Nutritional Quality Index (ONQI) Mean of the distribution 17.5 ± 0.2 Percentiles of the distribution Lowest quartile breakpoint 9.9 ± 0.1 Middle quartile breakpoint (median) 13.8 ± 0.2 Highest quartile breakpoint 20.4 ± 0.3 HundredScale - NuVal 0-100 Scale Mean of the distribution 26.5 ± 0.1 Percentiles of the distribution Lowest quartile breakpoint 23.9 ± 0.1 Middle quartile breakpoint (median) 25.4 ± 0.1 Highest quartile breakpoint 28.0 ± 0.1 Percentage (%) distribution for the population 0 - 19 4.1 ± 0.3 20 - 39 92.5 ± 0.4 40 - 49 3.2 ± 0.3 60 - 100 0.2 ± 0.1 1 Source: NHANES, 2003-2006, ages 4 yr and older, Day 1 (n = 15,900) ONQI and HundredScale values were determined without the glycemic load coefficient for diets using composite method. 2 Mean, percentile breakpoints, percentage and standard errors estimated using SUDAAN.

In press: Am J Clin Nutr; 4/10

Table 6. Linear regression to correlate ONQI and HundredScale with Healthy Eating Index (HEI-2005)1 P-value Model

Beta SE T-test P-value R-Square2

Independent Variable Coeff. Beta H0: =0 Wald F Wald F (%) Overall Nutritional Quality Index (ONQI) 0.53 0.02 0.000 588.6 0.000 29.30% HundredScale - NuVal 0-100 Scale 1.12 0.03 0.000 1183.4 0.000 27.57% 1 Source: NHANES, 2003-2006, ages 4 yr and older, Day 1 (n = 15,900) ONQI and HundredScale values were determined without the glycemic load coefficient for diets using composite method. 2 Covariates include gender, age (years), and race-ethnicity

NuVal™ at the Harvard School of Public Health

A sneak preview of findings from the

Nurses Health Study & the Health Professionals Follow-up

Study

January, 2010

Methods-

Independent research by Dr. Walter Willett and his team at the Harvard School of Public Health

Facilitation by the ONQI team at the Yale Prevention Research Center

The ONQI algorithm was provided to the Harvard team

Methods, cont-

ONQI algorithm used to assign a NuVal score to every food item included in the food frequency questionnaire administered in the Nurses Health Study and Health Professionals Follow-up Study in 1986

Data collection for subsequent years now on-going

NuVal scores for individual food items were then weighted by frequency (i.e., number of servings)

Methods, cont-

NuVal scores were aggregated to the level of total diet, divided into quintiles

Multivariate models adjusted for: age, calories, smoking, BMI, aspirin use, exercise, vitamin E

supplementation, menopausal status, menopausal hormone use, family history of MI or cancer, and history of high cholesterol or blood pressure

Nurses Health Study: NuVal vs. HEI-2005; n = ~70,000

NuVal, Quintile 5

HEI-2005, Quintile 5

RR of chronic disease 0.86 (0.82-0.90) 0.88 (0.83-0.92)

RR of CVD 0.77 (0.69-0.86) 0.83 (0.75-0.93)

RR of diabetes 0.79 (0.71-0.87) 0.90 (0.81-1.00)

RR of cancer 1.00 (0.93-1.07) 0.92 (0.86-0.98)

HPFS: NuVal vs. HEI-2005; n = ~40,000

NuVal, Quintile 5

HEI-2005, Quintile 5

RR of chronic disease 0.85 (0.81-0.90) 0.86 (0.81-0.92)

RR of CVD 0.77 (0.69-0.85) 0.80 (0.72-0.89)

RR of diabetes 0.77 (0.67-0.88) 0.94 (0.82-1.08)

RR of cancer 0.99 (0.91-1.09) 0.93 (0.84-1.03)

Eating to live…

RR of all-cause mortality, top vs. bottom quintile of NuVal scores

NHS: RR = 0.88; p<0.001 (n ~ = 70,000) HPFS: RR = 0.87; p = 0.001 (n ~ = 40,000)

Conclusions:

Despite limitations in the analysis that bias the performance of NuVal toward the null, NuVal was a slightly betterbetter predictor of total chronic disease risk & all-cause mortality than the HEI-2005 in 70,000 women and 40,000 men

To the best of our knowledge, this is the highest validation standard achieved by any nutritional profiling system

Additional data analysis at Harvard is on-going

Other research collaborations-

UCLA University of Iowa; STAR Registry University College Cork, Ireland Michigan State University Oxford University, England

The Nu value proposition

Not dollars earned per calorie (supply) Not calories purchased per dollar

(demand) But…

overall nutrition per dollar, and dollars per overall nutrition

Less far-fetched than urban legend would suggest…

Item Type Type N Mean SD p value

Bread

Less nutritious 8 $2.56 $.80 0.03

More nutritious 9 $3.36 $.28

Cereal Bars (cost/serving)

Less nutritious 9 $.64 $.48 0.05

More nutritious 8 $.53 $.04

Cereal

Less nutritious 9 $3.50 $.30 <0.01

More nutritious 9 $2.46 $.69

Chips

Less nutritious 9 $2.87 $.79 0.06

More nutritious 8 $2.17 $.58

Cookies

Less nutritious 9 $3.40 $.37 <0.01

More nutritious 8 $2.76 $.50

Crackers

Less nutritious 9 $2.56 $.62 0.70

More nutritious 8 $2.69 $.36

Juices (cost/serving)

Less nutritious 8 $.26 $.09 0.07

More nutritious 7 $.83 $1.39

Peanut Butter

Less nutritious 7 $2.37 $.24 0.07

More nutritious 6 $3.67 $1.40

All Categories(cost/item)

Less nutritious 68 $2.29 $1.26

0.76More nutritious 63 $2.31 $1.24

Table 1. Mean costs of more nutritious and less nutritious items

Under Review: Public Health Nutrition, 2/10

Money where mouths are? It’s a SNAP Directly link measure of nutritional quality to

purchasing power of food stamps In any given food category (e.g., bread), use NuVal

scores to stratify into quartiles For foods purchased in bottom quartile of overall

nutritional quality, $1 of vouchers would be worth $1 $1.25 in next quartile $1.50 in next quartile $2 in top quartile

Concept applicable to any assistance program or to public at large via public/private partnership involving retailers and loyalty card programs

Sustainability, Viability, Vitality; Citius, Altius, Fortius and our Olympic moment

of rings, links, chains and circles

Rethinking the links in the food chain… To create a virtuous circle:

More wholesome foods are readily identifiable by all

Incentives encourage selection of more wholesome foods; nutrition per dollar is the new measure of value

Incentives from health sector lower care costs, and support shift in sales to keep Ag profits steady

Shift to less processed foods (‘mostly plants’) enhances sustainability, benefits environment

Sustainability, viability, vitality: everybody wins

The falsely alluring alternatives to eating well…

Pharmacotherapeutic Phantasies & Cold Hard Steel-

EU suspends sales of rimonabant: 10/24/08 Tesofensine shows promise, but… And then there’s brown fat:

April 12, 2009 Editorial: Cool Way to Lose Weight?

Obesity Surgery Increases by 600 Percent Safer Techniques, More Insurance Coverage and Celebrity Patients Make It

More Appealing ABC News Medical Unit, May 31, 2006

Beware our Birthmark…

Like Hawthorne’s hapless heroine, we all are marked from birth…

Katz DL. The Scarlet Burger. Wall Street Journal, Op-Ed. 11/19/03

The one TRUE Path-

Thank you!

David L. Katz, MD, MPH, FACPM, FACPDirector, Yale Prevention Research CenterPresident, Turn the Tide Foundation, Inc.

130 Division St.Derby, CT 06418(203) 732-1265

David.katz@yale.edu

www.davidkatzmd.com